scholarly journals A Formal Approach to Verify Parameterized Protocols in Mobile Cyber-Physical Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Long Zhang ◽  
Wenyan Hu ◽  
Wanxia Qu ◽  
Yang Guo ◽  
Sikun Li

Mobile cyber-physical systems (CPSs) are very hard to verify, because of asynchronous communication and the arbitrary number of components. Verification via model checking typically becomes impracticable due to the state space explosion caused by the system parameters and concurrency. In this paper, we propose a formal approach to verify the safety properties of parameterized protocols in mobile CPS. By using counter abstraction, the protocol is modeled as a Petri net. Then, a novel algorithm, which uses IC3 (the state-of-the-art model checking algorithm) as the back-end engine, is presented to verify the Petri net model. The experimental results show that our new approach can greatly scale the verification capabilities compared favorably against several recently published approaches. In addition to solving the instances fast, our method is significant for its lower memory consumption.

10.29007/68dk ◽  
2019 ◽  
Author(s):  
Gidon Ernst ◽  
Paolo Arcaini ◽  
Alexandre Donzé ◽  
Georgios Fainekos ◽  
Logan Mathesen ◽  
...  

This report presents the results from the 2019 friendly competition in the ARCH workshop for the falsification of temporal logic specifications over Cyber-Physical Systems. We describe the organization of the competition and how it differs from previous years. We give background on the participating teams and tools and discuss the selected benchmarks and results. The benchmarks are available on the ARCH website1, as well as in the competition’s gitlab repository2. The main outcome of the 2019 competition is a common benchmark repository, and an initial base-line for falsification, with results from multiple tools, which will facilitate comparisons and tracking of the state-of-the-art in falsification in the future.


Author(s):  
Fulong Chen ◽  
Yuqing Tang ◽  
Canlin Wang ◽  
Jing Huang ◽  
Cheng Huang ◽  
...  

2017 ◽  
Vol 11 (4) ◽  
pp. 2614-2627 ◽  
Author(s):  
Xi Zheng ◽  
Christine Julien ◽  
Miryung Kim ◽  
Sarfraz Khurshid

2015 ◽  
Author(s):  
Rodrigo Goulart ◽  
Juliano De Carvalho ◽  
Vera De Lima

Word Sense Disambiguation (WSD) is an important task for Biomedicine text-mining. Supervised WSD methods have the best results but they are complex and their cost for testing is too high. This work presents an experiment on WSD using graph-based approaches (unsupervised methods). Three algorithms were tested and compared to the state of the art. Results indicate that similar performance could be reached with different levels of complexity, what may point to a new approach to this problem.


Author(s):  
Jiayi Su ◽  
Yuqin Weng ◽  
Susan C. Schneider ◽  
Edwin E. Yaz

Abstract In this work, a new approach to detect sensor and actuator intrusion for Cyber-Physical Systems using a bank of Kalman filters is presented. The case where the unknown type of the intrusion signal is considered first, using two Kalman filters in a bank to provide the conditional state estimates, then the unknown type of intrusion signal can be detected properly via the adaptive estimation algorithm. The case where the target (either sensor or actuator) of the intrusion signal is unknown is also considered, using four Kalman filters in a bank designed to detect if the intrusion signal is about to affect healthy sensor or actuator signal. To test these methods, a DC motor speed control system subject to attack by different types of sensor and actuator signals is simulated. Simulations show that different types of sensor and actuator intrusion signals can be detected properly without the knowledge of the nature and the type of these signals.


Author(s):  
Xiang Kong ◽  
Qizhe Xie ◽  
Zihang Dai ◽  
Eduard Hovy

Mixture of Softmaxes (MoS) has been shown to be effective at addressing the expressiveness limitation of Softmax-based models. Despite the known advantage, MoS is practically sealed by its large consumption of memory and computational time due to the need of computing multiple Softmaxes. In this work, we set out to unleash the power of MoS in practical applications by investigating improved word coding schemes, which could effectively reduce the vocabulary size and hence relieve the memory and computation burden. We show both BPE and our proposed Hybrid-LightRNN lead to improved encoding mechanisms that can halve the time and memory consumption of MoS without performance losses. With MoS, we achieve an improvement of 1.5 BLEU scores on IWSLT 2014 German-to-English corpus and an improvement of 0.76 CIDEr score on image captioning. Moreover, on the larger WMT 2014 machine translation dataset, our MoSboosted Transformer yields 29.6 BLEU score for English-toGerman and 42.1 BLEU score for English-to-French, outperforming the single-Softmax Transformer by 0.9 and 0.4 BLEU scores respectively and achieving the state-of-the-art result on WMT 2014 English-to-German task.


2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Yongzhen Guo ◽  
Baijing Han ◽  
Weiping Wang ◽  
Manman Yuan

This paper is concerned with the security state estimation and event-triggered control of cyber-physical systems (CPSs) under malicious attack. Aiming at this problem, a finite-time observer is designed to estimate the state of the system successfully. Then, according to the state information, the event-triggered controller is designed through the event-triggered communication. It is proved that the system is uniformly and finally bounded. Finally, the effectiveness of the proposed method is verified by a simulation example.


Author(s):  
Tianxing Wu ◽  
Guilin Qi ◽  
Bin Luo ◽  
Lei Zhang ◽  
Haofen Wang

Extracting knowledge from Wikipedia has attracted much attention in recent ten years. One of the most valuable kinds of knowledge is type information, which refers to the axioms stating that an instance is of a certain type. Current approaches for inferring the types of instances from Wikipedia mainly rely on some language-specific rules. Since these rules cannot catch the semantic associations between instances and classes (i.e. candidate types), it may lead to mistakes and omissions in the process of type inference. The authors propose a new approach leveraging attributes to perform language-independent type inference of the instances from Wikipedia. The proposed approach is applied to the whole English and Chinese Wikipedia, which results in the first version of MulType (Multilingual Type Information), a knowledge base describing the types of instances from multilingual Wikipedia. Experimental results show that not only the proposed approach outperforms the state-of-the-art comparison methods, but also MulType contains lots of new and high-quality type information.


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